Build vs.Buy Data Pipelines: A Detailed Discussion
Leaders let “DATA” decide, Laggards let intuition!
What color the new product packaging should be, or what age-group should be targeted in the next Facebook Ad campaign, more and more decisions are becoming data-dependent.
Businesses are spending millions of dollars in collecting, transforming, and analyzing more and minute “DATA” every year, in hopes of gaining access to crucial insights. With data pouring in from hundreds of sources every single day, manual integration becomes a burden on a firm’s assets. This is when organizations start looking into Automated Data Pipelines.
Automated Data Pipelines
In layman’s terms, a data pipeline constitutes a series of transformational steps that extract raw data from its source and enable its flow into an appropriate destination (likely to be a data lake or a data warehouse). During this journey, the data is filtered & transformed into a format that can be further used for analysis and reporting of crucial business insights. Data pipelines not only ensure a continuous and reliable flow of data into the various organizational storage and analysis subsystems but also monitors the data for accuracy and loss. By employing a well-designed data pipeline, you can ensure access to relevant information in due time to make critical decisions for ensuring business’ success & survival.
Once you decide to incorporate data pipelines, the next obvious question is –
Which is better – Building data pipelines or Buying them?
Single Line Answer – Get an off-the-shelf solution!
Building data pipelines is costly, has a high opportunity cost, and will consume time and efforts that can be otherwise employed in core expertise.
WHY ? – The same reason why a sportsperson is only concerned about perfecting his/her game and not how sports equipment is manufactured.
But, if you are still contemplating between the building and buying of data pipelines, let’s deliberate over a few key factors that can help you decide.
Most business decisions come down to choosing between a costly and a not-so-costly option, let’s discuss which data pipeline will be more budget-friendly for your business.
To build a data pipeline from scratch, you will need a dedicated team of data engineers at your disposal and invest a substantial amount in purchasing and maintaining the technological infrastructure required to build. These days, a data engineer’s salary is easily upwards of 100k/year and you would require at least 4 to 7 of them for building and maintaining hundreds of data pipelines. On the other hand, the cost of buying an off-the-shelf data integration solution is only a fraction of what you invest in building data pipelines. For getting an accurate estimate of your data integration costs you can talk to the experts.
Time – Build vs. Buy
Building data pipelines is not a small feat. Generally, it takes somewhere between one to three weeks [Exact time depends on the source and the format in which it provides data] for a developing team to set up a single rudimentary pipeline. This includes time spent in building a capable team, getting the required technical infrastructure in place, and the actual building & testing time.
Therefore, even if you choose to build data pipelines, it is probable that the deploying time will be nothing short of a few months if not years. Whereas, an off-the-shelf solution (Like DataChannel) reduces this time to only a few minutes. With DataChannel in place, you can immediately start leveraging insights.
Effort – Build vs. Buy
Building a data pipeline will require you to obtain developer access to diverse data resources (explicit permissions are sought for external sources and the source list would easily consist of 30+ sources for most firms), explore the data which would be handled by the pipeline, schema design, set up a connector framework, test and validate.
Building a pipeline once might seem easy, its maintenance, however, is an indefinite endeavor. You have to be constantly vigilant for updates in the underlying data sources and once that happens, the above cycle repeats itself. All this amounts to wasted efforts in the long run, and it makes more sense to outsource data pipeline building and maintenance to a third party.
Customization? – Building pipelines makes more sense!
There is no doubt that every business requirement is unique and building in-house pipelines make more sense. Especially, when it comes to handling specific use cases, a vendor solution stands to disappoint you.
However, consider these –
- Most SaaS solutions have much deeper capabilities than you might be able to comprehend at an initial glance.
- The vendor has years of knowledge and experience in the field, a dedicated team of experts at his/her disposal, and he/she would be responsible for upgrades.
- Also, there exists an inherent bias against buying a SaaS solution instead of building one
Building pipelines is something you can always venture into, however, with so many customization options available in on-the-shelf solutions, you can always choose to opt for tailor-made data pipelines. Therefore, before closing doors on a third-party solution, give DataChannel a try. This way, you can be sure whether this solution adequately meets your requirement or you need to build your own data pipelines from scratch.
[EDITOR NOTE: To get yourself a customized yet powerful data pipeline solution right away, contact DataChannel right away. ]
Scalability & Upgrades?
As consumers and marketing methods continue to evolve, new data sources will proliferate your business processes, necessitating their inclusion in your data source list. This will be highly beneficial for maximizing insight accuracy and reducing analysis errors. However, you will have no choice but to burden your data engineering team for integrating more and more data resources more often.
Even if you manage to handle that, events like frequent data source changes, the inclusion of new sources, unpredictable growth in amounts and variety of data, etc. will exhaust your team and burden your resources. Strategizing and planning for such events will be added to your to-do list as well. To summarise, it is conventional to outsource non-core functions such as data ETL and analysis, and you should benefit from the same.
With an off-the-shelf solution like DataChannel, you can expect infinite scalability options. Their team will be responsible for data source upgrades, source diversity, scalability, etc., all you need to do is use the derived insights.
What about issues like Reliability, Security, & Privacy?
For security and privacy reasons having complete control and visibility of your data is critical. Data will need protection from both internal and external threats like corruption, leaks, permission errors, etc. Therefore, building an in-house pipeline seems viable.
But consider this –
Now and then, data pipelines will suffer from issues like data delays, changing schema, changing volumes, pipeline failures, security & privacy breaches, incomplete transactions, etc., which can render the data useless or worse – harmful for your organization. The problem of maintaining data reliability, integrity, security, and privacy is a continuous and expert-level problem. Now, with your team engaged in core activities, you can not rely on their expertise, and their presence every single time such a problem comes up, and hiring a separate team for such purposes is not budget-friendly.
The middle path would be opting for an off-the-shelf solution like DataChannel, where their team is responsible for handling such issues and additionally they maintain strict adherence to international security and privacy guidelines.
Get the best of both worlds with DataChannel
Data is dear to businesses and it is important to deliberate well before choosing between building vs buying data pipelines for your organization. You can choose DataChannel to harness the power of big-data analytics by empowering your team with the DATA that is logically linked, frequently updated, and automatically maintained into a warehouse of your choice with the help of their pre-built 100+ data pipelines.
Let us look at some of the features offered by DataChannel, in light of what we discussed above.
- It offers an interactive, easy-to-understand, and user-friendly interface. Therefore, you don’t need to hire and train a specialist for handling the platform, just kick-start data integration with some simple clicks within minutes.
- DataChannel is a fully automated and zero-code platform, which doesn’t require you to waste long hours and effort in writing hefty scripts for data ETL.
- It supports 100+ connectors spanning a wide range of on-cloud and on-premise sources like social media, CRM, sales, flat files, etc. You can even request specific business customization as per your needs.
- With DataChannel you are free to choose between a Data Warehouse owned and maintained by DataChannel, a third-party vendor, or your in-house team. In every case, you will have complete control and possession of your data.
- Hours of tedious schema upkeep is not your job anymore, DataChannel delivers data ready for analysis via Standardized Schema support.
- DataChannel enables you to connect to a variety of BI tools to your data warehouse for visualization or analytics modeling.
- You will always find a helpful data-partner in DataChannel, with their excellent Customer Support.
Whether you choose to build or buy data pipelines, you must never compromise on attributes like scalability, reliability, security, integrity, privacy, time and effort spent, cost, etc. to find your best fit.
It is unwise to use a sword in place of a needle. You have a lot on your plate already, and building data pipelines will require a great deal of effort, time, money, and experience.
Even deliberating alternatives and choosing what works best for you will take time, meanwhile, why don’t you let DataChannel tend to your data. DataChannel offers a 14-day FREE trial [A try-before-you-buy feature positively reflects on the confidence of its developers in the efficacy of their product].